from sklearn.svm import SVC
from sklearn.model_selection import GridSearchCV

svc = SVC()
parameters = [
    {
        'C': [1, 3, 5, 7, 9, 11, 13, 15, 17, 19],
        'gamma': [0.00001, 0.0001, 0.001, 0.1, 1, 10, 100, 1000],
        'kernel': ['rbf']
    },
    {
        'C': [1, 3, 5, 7, 9, 11, 13, 15, 17, 19],
        'kernel': ['linear']
    }
]
clf = GridSearchCV(svc, parameters, cv=5, n_jobs=8)
clf.fit(train_data, train_data_tag)
print(clf.best_params_)
best_model = clf.best_estimator_
best_model.predict(test_data)